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Sustainable Development and Application in Autonomous Driving System for Better Mobility

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 6131

Special Issue Editors

Dr. Chao Gu

E-Mail Website
Guest Editor
Academy of Arts & Design, Tsinghua University, Beijing 100084, China
Interests: user behavior; interaction design; interactive experience
Dr. Chen-Chiung Hsieh

E-Mail Website
Guest Editor
Department of Computer Science and Engineering, Tatung University, Taipei City 104, Taiwan
Interests: artificial intelligence; database design; pattern recognition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of autonomous driving technology is progressing at an unprecedented pace, and new forms of control systems are assisting user behavior in traffic in numerous ways. This Special Issue aims to address complex transportation problems and tackle existing challenges through interdisciplinary discussions centered around technology. Topics of interest include, but are not limited to, congestion, pollution, and travel strategies. Additionally, we focus on the specific needs of various demographic groups in relation to autonomous driving features, such as gender, age, individuals with visual or hearing impairments, and the autism community. By enhancing the design effectiveness of autonomous driving systems and improving the overall operation of the transportation system in these diverse contexts and user needs, we aim to contribute to the promotion of sustainable development goals.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Sustainable transportation application innovations;
  • Human–machine interaction in autonomous driving;
  • Basis for policy making;
  • Needs of special users;
  • Intelligent solutions in transportation;
  • Data-driven design methods for autonomous driving;
  • Advanced industrial engineering;
  • Management in the manufacturing process;
  • Sustainability of future technologies.

We look forward to receiving your contributions.

Dr. Chao Gu
Dr. Chen-Chiung Hsieh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable development
  • Industry 4.0
  • human–machine interaction
  • industrial engineering
  • user behavior
  • innovation
  • management
  • policy
  • inclusive society
  • service design

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Published Papers (3 papers)

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Research

21 pages, 2846 KiB  
Article
Research on Multimodal Adaptive In-Vehicle Interface Interaction Design Strategies for Hearing-Impaired Drivers in Fatigue Driving Scenarios
by Dapeng Wei, Chi Zhang, Miaomiao Fan, Shijun Ge and Zhaoyang Mi
Sustainability 2024, 16(24), 10984; https://doi.org/10.3390/su162410984 - 14 Dec 2024
Cited by 1 | Viewed by 1710
Abstract
With the advancement of autonomous driving technology, especially the growing adoption of SAE Level 3 and above systems, drivers are transitioning from active controllers to supervisors who must take over in emergencies. For hearing-impaired drivers in a fatigued state, conventional voice alert systems [...] Read more.
With the advancement of autonomous driving technology, especially the growing adoption of SAE Level 3 and above systems, drivers are transitioning from active controllers to supervisors who must take over in emergencies. For hearing-impaired drivers in a fatigued state, conventional voice alert systems often fail to provide timely and effective warnings, increasing safety risks. This study proposes an adaptive in-vehicle interface that combines visual and tactile feedback to address these challenges. Experiments were conducted to evaluate response accuracy, reaction time, and cognitive load under varying levels of driver fatigue. The findings show that the integration of visual and tactile cues significantly improves takeover efficiency and reduces mental strain in fatigued drivers. These results highlight the potential of multimodal designs in enhancing the safety and driving experience for hearing-impaired individuals. By providing practical strategies and evidence-based insights, this research contributes to the development of more inclusive and effective interaction designs for future autonomous driving systems. Full article
(This article belongs to the Special Issue Sustainable Development and Application in Autonomous Driving System for Better Mobility)
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24 pages, 797 KiB  
Article
Research on the Behavior Influence Mechanism of Users’ Continuous Usage of Autonomous Driving Systems Based on the Extended Technology Acceptance Model and External Factors
by Juncheng Mu, Linglin Zhou and Chun Yang
Sustainability 2024, 16(22), 9696; https://doi.org/10.3390/su16229696 - 7 Nov 2024
Cited by 2 | Viewed by 1620
Abstract
In recent years, with the advancement of urbanization and the increase in traffic congestion, the demand for autonomous driving has been steadily growing in order to promote sustainable urban development. The evolution of automotive autonomous driving systems significantly influences the progress of sustainable [...] Read more.
In recent years, with the advancement of urbanization and the increase in traffic congestion, the demand for autonomous driving has been steadily growing in order to promote sustainable urban development. The evolution of automotive autonomous driving systems significantly influences the progress of sustainable urban development. As these systems advance, user evaluations of their performance vary widely. Autonomous driving systems present both technological advantages and controversies, along with challenges. To foster the development of autonomous driving systems and facilitate transformative changes in urban traffic sustainability, this research aims to explore user behavior regarding the continued use of autonomous driving systems. It is based on an extended technology acceptance model, examining the impacts of user scale, perceived importance, post-experience regret, user driving habits, and external factors on the intention to continue using these systems. The conclusions are as follows. (1) A model design is constructed that uses user scale, perceived importance, and regret after experience as antecedent variables, with user driving habits as a mediating variable to explain the intention to continue using autonomous driving systems, demonstrating a degree of innovation. (2) It is verified that user driving habits are a key factor determining the intention to continue using these systems, highlighting the importance of user habits in the application of autonomous driving systems. (3) Perceived importance significantly affects both user driving habits and the intention to continue using the system, while regret after experience has a significant negative correlation only with habit formation and does not directly affect the intention to continue use, indicating that users are more concerned with the actual functionality and practicality of the system. (4) User scale is shown to indirectly influence the intention to continue using through various pathways, providing a new perspective for related theoretical research. (5) Aside from safety capabilities, other external factors such as economic benefits and technological stability significantly influence the intention to continue using, while the lack of significance for safety capabilities may be due to users trusting their own driving skills in critical moments. (6) The research results offer valuable references for the improvement and promotion of autonomous driving systems, emphasizing the practicality and usability of the system. (7) This study provides a new theoretical framework for the application of habit theory and regret theory in related fields. Therefore, through empirical analysis, this research delves into the key factors influencing the intention to continue using autonomous driving systems, offering certain reference value for the development of autonomous driving systems and contributing to their theoretical development and practical application. Full article
(This article belongs to the Special Issue Sustainable Development and Application in Autonomous Driving System for Better Mobility)
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20 pages, 816 KiB  
Article
How to Promote the Adoption of Electric Robotaxis: Understanding the Moderating Role of Inclusive Design on Interactive Features
by Chao Gu, Lie Zhang and Yingjie Zeng
Sustainability 2024, 16(20), 8882; https://doi.org/10.3390/su16208882 - 14 Oct 2024
Cited by 3 | Viewed by 2045
Abstract
In recent years, China has witnessed a growing trend in the adoption of electric robotaxi services, with an increasing number of users beginning to experience this emerging mode of transportation. However, enhancing user willingness to ride remains a core challenge that the electric [...] Read more.
In recent years, China has witnessed a growing trend in the adoption of electric robotaxi services, with an increasing number of users beginning to experience this emerging mode of transportation. However, enhancing user willingness to ride remains a core challenge that the electric robotaxi industry urgently needs to address. Our study approached this issue from the perspective of interactive features, surveying 880 respondents and utilizing structural equation modeling to analyze user preferences. The research findings indicate that computer-based entertainment has a significant positive impact on traffic information completeness and social interaction, with a large effect (β > 0.5, p < 0.05), and it also exerts a small positive effect on behavioral intention (β > 0.1, p < 0.05). Traffic information completeness and social interaction have a medium positive effect on behavioral intention (β > 0.3, p < 0.05). In addition, we confirmed that inclusive design, gender, and age have significant moderating effects. Understanding the impact of inclusive design on user behavior can help drive industry changes, creating a more inclusive human–vehicle interaction environment for people with different abilities, such as those with autism. Our study reveals the key factors influencing users’ willingness to ride and offers insights and recommendations for the development and practical application of interactive features in electric robotaxis. Full article
(This article belongs to the Special Issue Sustainable Development and Application in Autonomous Driving System for Better Mobility)
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